title: Sparsity-based super-resolution and phase-retrieval in waveguide arrays.
abstract: We present a scheme for recovering the complex input field launched into a waveguide array, from partial measurements of its output intensity, given advance knowledge that the input is sparse. In spite of the fact that in general the inversion problem is ill-conditioned, we demonstrate experimentally and in simulations that the prior knowledge of sparsity helps overcome the loss of information. Our method is based on GESPAR, a recently proposed efficient phase retrieval algorithm. Possible applications include optical interconnects and quantum state tomography, and the ideas are extendable to other multiple input and multiple output (MIMO) communication schemes.
authors.forename: Yoav
authors.initials: Y
authors.lastname: Shechtman
authors.forename: Eran
authors.initials: E
authors.lastname: Small
authors.forename: Yoav
authors.initials: Y
authors.lastname: Lahini
authors.forename: Mor
authors.initials: M
authors.lastname: Verbin
authors.forename: Yonina C
authors.initials: YC
authors.lastname: Eldar
authors.forename: Yaron
authors.initials: Y
authors.lastname: Silberberg
authors.forename: Mordechai
authors.initials: M
authors.lastname: Segev